Fake reviews detection and its impact on trust and purchase intention: the context of Vietnamese platform economy

Abstract

In the digital era, e-commerce is one of the fastest-growing shopping platforms, and online reviews play a critical role in generating intentions and making purchase decisions on digital platforms. Grasping that mentality, a series of positive or negative fake reviews to increase competition appeared, confusing information for customers. Therefore, studies aimed at verifying the reliability of online reviews or identifying factors to detect phony reviews are gradually becoming more popular and researched in many fields with different research methods. Hence, with the purpose of creating a better buying experience for customers on e-commerce platforms, especially in Vietnam, the authors researched the topic: “Fake reviews detection and its impact on trust and purchase intention: The context of Vietnamese platform economy”. The present study addresses two questions: “On what factors do consumers rate and filter online reviews as real or fake?”, “Whether detecting fake reviews affects consumer trust and purchase intention?”. The study was carried out by two methods: qualitative and quantitative research. The survey object was customers who have experienced buying on e-commerce platforms, conducted on 20 respondents (qualitative research) and 221 respondents (quantitative research).The results of analysis using the PLS-SEM technique show that 4 out of 6 factors in the model influence the detection of fake reviews, including inconsistency, review length, emotional cues, and consumers' product knowledge. In this research, the authors propose an AI system to distinguish and filter fake reviews on e-commerce platforms, and at the same time, continue to study and explore other factors that have a stronger effect on detecting deceptive reviews to improve the operational efficiency of the detection system, as well as increasing consumers' understanding of the current situation of fake reviews.